What is Deep Learning?

Deep learning is a type of machine learning in which computers form large artificial neural networks that resemble those found in the human brain.

Deep learning definition

In deep learning, large artificial neural networks are fed learning algorithms and ever-increasing amounts of data, continuously improving their ability to "think" and "learn" the more data they process. "Deep" refers to the many layers the neural network accumulates over time, and performance improves the deeper the network gets. While most deep learning is currently done with human supervision, the aim is to create neural networks that are able to train themselves and "learn" independently.

Why deep learning?

Neural nets have been around since the 1950s, but only in recent years have both computational power and data storage capabilities advanced to the point where deep learning can be used to create exciting new technologies.

While most enterprises have yet to incorporate deep learning into their business processes or products, this type of machine learning is behind "smart" technology ranging from voice- and image-recognition software to self-driving cars. Advances in deep learning and robotics may soon lead to smart medical imaging technology that can reliably make diagnoses, self-piloting drones, and self-maintaining machinery and infrastructure of all kinds.

Consume your deep learning infrastructure using a flexible, on-demand consumption model. Get scalable capacity as needed, paying only for what you use, including servers, storage, networks, software, and services.

Weather prediction is not a perfect science, but recent advancements in computing technologies combined with the growing availability of weather-related data has served to dramatically improve the accuracy of forecasts.